Background: Cortical reorganization occurs in the adult central nervous system. Plasticity contributes to various forms of human behavior including motor learning and memory formation, consolidation, reconsolidation and short and long term retention. It is very important to understand the role of these different behavioral processes and of the mechanisms underlying these various forms of human plasticity during skill acquisition. Findings this year: Several important advances were implemented during this time period with regard to our better understanding the mechanisms of human motor neuroplasticity and the development of strategies to enhance it in healthy subjects. Most recently, we advanced our understanding of reconsolidation in the human motor cortex by demonstrating that primary cortical processing in the human brain interacting with pre-existent reactivated memory traces is critical for successful modification of the existing related memory. In relation to the influence of reward on motor learning, we found that training under rewarded conditions is more effective than training under punished or neutral conditions in eliciting lasting motor learning, an advantage driven by offline memory gains that persist over time. This finding may impact the way in which training protocols are designed in education but also in neurorehabilitation after brain lesions such as stroke or traumatic brain injury. We have also probed for hemispheric specialization in the effects of transcranial direct current stimulation (tDCS) applied over the primary motor cortex (M1) on motor learning. Six groups trained for 3 sessions on a visually-guided sequential pinch force modulation task with their right or left hand, and received right M1, left M1, or sham tDCS. A linear mixed model analysis for motor skill showed a significant main effect for the stimulation group (left M1, right M1, sham), but not for hand (right, left) or their interaction. Left M1 tDCS induced significantly greater skill learning than sham when hand data were combined, a result consistent with the hypothesized left hemisphere specialization for motor skill learning, but also with possible increased left M1 responsiveness to tDCS. The unihemispheric montage effect size was half that of the more common montage, and subsequent power analysis indicated that 75 subjects per group would be needed to detect differences seen with only 12 subjects with the customary bihemispheric montage. Interestingly, despite its increasing use in experimental and clinical settings, the cellular and molecular mechanisms underlying transcranial direct current stimulation (tDCS) remain unknown. Anodal tDCS applied to human motor cortex (M1) improves motor skill learning, suggesting a role for synaptic plasticity. In one study, we demonstrated in mouse M1 slices that DCS induces a long-lasting synaptic potentiation (DCS-LTP), which is polarity-specific, NMDA-receptor dependent and requires coupling of DCS with repetitive low-frequency synaptic activation (LFS). BDNF is a key mediator of this phenomenon, as combined DCS and LFS enhance BDNF-secretion and TrkB-activation, and DCS-LTP is absent in BDNF and TrkB mutant mice. Moreover, the BDNF val66met polymorphism known to partially affect activity-dependent BDNF secretion, impairs motor skill acquisition in humans and mice. Motor learning is enhanced by anodal tDCS, as long as activity-dependent BDNF secretion is in place. We proposed that tDCS may improve motor skill learning by augmenting synaptic plasticity that requires BDNF-secretion and TrkB-activation within M1. One important area of research lies in identifying the white matter microstructural correlates of superior long-term skill gained under randomized rather than blocked practice schedules. In one study relating diffusion-weighted imaging with learning, we demonstrated that randomized practice schedules improve long-term implicit skill more than grouped practice schedules, and more importantly from a mechanistic point of view, that the superior skill acquired through randomized practice can be related to white matter microstructure in the sensorimotor corticostriatal network.